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. 2011 Jun 25;11:499. doi: 10.1186/1471-2458-11-499

Assessing the association between all-cause mortality and multiple aspects of individual social capital among the older Japanese

Jun Aida 1,2,✉, Katsunori Kondo 3, Hiroshi Hirai 3, S V Subramanian 4, Chiyoe Murata 5, Naoki Kondo 6, Yukinobu Ichida 3, Kokoro Shirai 4,7, Ken Osaka 2
PMCID: PMC3144463  PMID: 21702996

Abstract

Background

Few prospective cohort studies have assessed the association between social capital and mortality. The studies were conducted only in Western countries and did not use the same social capital indicators. The present prospective cohort study aimed to examine the relationships between various forms of individual social capital and all-cause mortality in Japan.

Methods

Self-administered questionnaires were mailed to subjects in the Aichi Gerontological Evaluation Study (AGES) Project in 2003. Mortality data from 2003 to 2008 were analyzed for 14,668 respondents. Both cognitive and structural components of individual social capital were collected: 8 for cognitive social capital (trust, 3; social support, 3; reciprocity, 2) and 9 for structural social capital (social network). Cox proportional hazard models stratified by sex with multiple imputation were used. Age, body mass index, self-rated health, current illness, smoking history, alcohol consumption, exercise, equivalent income and education were used as covariates.

Results

During 27,571 person-years of follow-up for men and 29,561 person-years of follow-up for women, 790 deaths in men and 424 in women were observed. In the univariate analyses for men, lower social capital was significantly related to higher mortality in one general trust variable, all generalised reciprocity variables and four social network variables. For women, lower social capital was significantly related to higher mortality in all generalised reciprocity and four social network variables. After adjusting for covariates, lower friendship network was significantly associated with higher all-cause mortality among men (meet friends rarely; HR = 1.30, 95%CI = 1.10-1.53) and women (having no friends; HR = 1.81, 95%CI = 1.02-3.23). Among women, lower general trust was significantly related to lower mortality (most people cannot be trusted; HR = 0.65, 95%CI = 0.45-0.96).

Conclusions

Friendship network was a good predictor for all-cause mortality among older Japanese. In contrast, mistrust was associated with lower mortality among women. Studies with social capital indices considering different culture backgrounds are needed.

Background

Few prospective cohort studies have assessed the association between social capital and mortality [1-5]. The studies did not use the same social capital indicators [1-5]. Some of these studies used proxy measures of social capital [6,7], such as crime rate [1], electoral participation [1,5] or volunteer activity [3-5]. There are several components of social capital, such as social network, participation, trust, reciprocity and volunteering [8]. Previous studies on social capital and mortality did not simultaneously use various components of social capital and their results were not fully consistent. In Finland, the association between mortality and individual social capital variables obtained by factor analysis (leisure participation, interpersonal trust and residential stability) was examined [2]. In men, leisure participation was associated with reduced all-cause mortality. In women, leisure participation and interpersonal trust were associated with reduced all-cause mortality. In a Swedish study, survival analyses showed that both neighbourhood social capital variables (election participation rate and crime rate) were significantly associated with mortality for males older than 65 years old but not for females [1]. Another study showed that living in a neighbourhood with the lowest level of social capital (volunteering, participation, political activities) was associated with significantly higher mortality than living in a neighbourhood with the highest level of social capital in England [5]. In contrast, among adults diagnosed and hospitalized with serious illnesses in the U.S, neighbourhood social capital (network density) was detrimental [4]. In addition, other neighbour social capital variables (social support, participation, volunteering, violence) did not significantly affect mortality [4]. In New Zealand, non-significant associations between neighbourhood social capital (volunteering) and mortality for both male and female were observed [3].

Studies on mortality and social capital have been conducted only in Western countries. However, social capital measurements developed in Western countries may not necessarily be equally applicable to Asian countries because of their different culture [9]. Although general trust has been broadly used as a measurement of social capital [10], it is known that intense ties within a family or group, often observed in collectivist cultures, prevent trust from developing beyond family or group boundaries [11-13]. In Japan, a relatively collectivist society with intense group ties, human relationships are based on mutual assurance within group members rather than mutual trust between members from different groups [11,13]. These cultural differences could potentially affect findings on the associations between social capital and health outcomes. In this respect, a social epidemiological study using various social capital indices in a non-Western cultural setting is important.

There is still debate about the precise definition and measurement of social capital [8,14,15]. Bourdieu defined social capital as "the aggregate of the actual or potential resources which are linked to possession of a durable network of more or less institutionalised relationships of mutual acquaintance and recognition"[16] and which focuses on the resources of individuals [8]. It is important to determine the association between individual social capital and health, because individual social capital indexes are components of aggregated measurements of community social capital [17]. Additionally, individual measures of social capital are not subject to the common problems arising from using area measurement in epidemiological studies, such as definition of a relevant areas [18,19]. No study has used various measures of individual social capital as a predictor of mortality in a non-Western country. The aim of the present prospective cohort study was to assess the influence of individual social capital on all-cause mortality among older Japanese.

Methods

Study population and procedure

The present analysis is based on the Aichi Gerontological Evaluation Study (AGES) Project data, an on-going prospective cohort study [20-24]. AGES investigates factors associated with the loss of health, including death and functional decline or cognitive impairment among older individuals. The study was undertaken in six municipalities covered the entire southern part of the Chita peninsula in Aichi Prefecture, Japan. During October one to 31 2003, a baseline mail questionnaire survey was administered. The follow-up started in November one 2003. Mortality data until May 2008 were obtained from 6 of the municipalities participating in AGES.

In 2003, there were 274,750 people living in the six municipalities, 17.9% of them being 65 years or older. The sample was restricted to people who did not already have physical or cognitive disabilities, defined as receiving public long-term care insurance benefits. From the municipalities, 29,374 community-dwelling, aged 65 years or over people were selected randomly. From this sample population, 14,804 people responded to the baseline survey. Of the 14,804 respondents, we could link the mortality data and baseline survey data on 14,668 subjects, because 91 were ineligible due to death, functional decline or cognitive impairment before November 1, 2003, and for a further 45 there was no information that would allow linking of the mortality data. Some subjects did not apply to certification of long-term care needs though they had limitations in basic activities of daily living including walking, bathing and toilet use. We excluded them from the analysis to avoid potential confounding (1,358 of the 14,668 respondents). Finally, 13,310 subjects (6,508 men and 6,802 women.) were included in the analysis for this cohort study. Figure 1 shows the study profile. Characteristics of participants at baseline have been reported elsewhere [23,24]. The AGES protocol was reviewed and approved by the ethics committee in Research of Human Subjects at Nihon Fukushi University.

Figure 1.

Figure 1

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Flowchart of the Aichi Gerontological Evaluation Study (AGES), Aichi, Japan, 2003-2008.

Social capital variables

Both cognitive and structural components [8,10,17,25] of individual social capital were used. We basically followed Harpham's classification of social capital [17]. We used eight cognitive social capital variables, including general trust, social support and generalised reciprocity, and nine structural social capital variables, including social networks.

Cognitive social capital

General trust was measured by 3 questions: "Generally speaking, would you say that most people can be trusted?", "Do you think most people would try to take advantage of you if they got a chance?" and "Would you say that most of the time people try to be helpful?". For all these questions, response alternatives were "yes", "it depends" and "no".

Social support was measured by three questions, using a dichotomous answering choice (yes/no): "Do you have someone who listens to your concerns and complaints?", "Do you have someone who looks after you when you are sick and stay in bed for a few days?" and "Do you have someone who acknowledges your existence and value?".

Generalised reciprocity was measured by two questions, again with a dichotomous choice (yes/no): "Do you listen to someone's concerns and complaints?" and "Do you look after someone when he/she is sick and stays in bed for a few days?".

Structural social capital

Participation in community activities was used as an indication of social network. Respondents were asked whether they belonged to a (i) political organization or group, (ii) industrial or trade association, (iii) volunteer group, (iv) citizen or consumer group, (v) religious organization or group, (vi) sports group or club, (vii) neighbourhood association / senior citizen club / fire-fighting team and (viii) leisure activity group.

Social network was also measured by the question "How often do you meet your friends?" (response options: "almost everyday", "twice or three times a week", "once a week", "once or twice a month", "several times a year", "rarely" or "I have no friends"). For analyses purposes, the first four response options were integrated into one category, named "once or more/month".

Covariates

We also asked about socio-demographic characteristics, lifestyle and health condition and included the following in the analyses as covariates: age, sex, self-reported body mass index (BMI), self-rated health, present illness, smoking history, alcohol consumption, exercise, equivalent income and educational attainment [23]. Self-reported BMI was categorized into 4 groups (less than 18.5, 18.5-24.9, 25-29.9, 30 or more). Self-rated health was measured by a single question, "What is your current health status?: Excellent; Good; Fair; Poor". Present illnesses and present medical treatment were surveyed as follows: "Are you currently receiving any medical treatment?: I have no illnesses or disabilities; I have illness(es) or disability(ies) but need no treatment at the moment; I discontinued treatment of my own decision; I am currently receiving some treatment. Smoking history was recorded in 3 categories (never, quit or current) and alcohol consumption into 4 categories (non-drinker, do not drinking everyday, drinking 35 g of alcohol or less daily, or drink more than 35 g every day). Subjects were asked about how many minutes a day they walk - the exercise variable; less than 30 minutes, 30-60, 60-90 or more than 90 minutes or more. Years of educational attainment was grouped as less than 6 years, 6-9 years, 10-12 years and 13 years or more. Household income and number of household members were recorded and then equivalent income was calculated and categorized in Yen: less than 1,500,000; 1,500,000-1,999,999; 2,000,000-2,499,999; 2,500,000-2,999,999; 3,000,000-3,499,999; 3,500,000-3,999,999; 4,000,000-4,999,999; 500,000,000 or higher.

Mortality outcome

Mortality obtained from the municipality government registry was treated as all-causes.

Analysis

We used Cox proportional hazard models to calculate the hazard ratio (HR) and 95% confidential intervals (95%CI) for all-cause mortality during the follow-up period. At first, we calculated univariate hazard ratios for mortality for the categories of each social capital variable. In the covariate adjusted models, we assessed the effect of each social capital variable on mortality with adjustment for age, BMI, self-rated health, current illness, smoking history, alcohol consumption, exercise, equivalent income and educational attainment. All analyses were stratified by sex.

In terms of analysis of missing data (numbers of missing responses in each variable are described in Table 1,2), we used the missing at random assumption for the relevant procedures. Multiple imputation with the MICE (multivariate imputation by chained equations) method in STATA was used [26]. Cox proportional hazard models were independently applied for 10 copies of the data, each with missing values suitably imputed. Estimates of the variables were calculated to give a single mean estimate and adjusted standard errors according to Rubin's rules [27]. HRs and 95%CI of the Cox proportional hazard models were calculated from these estimates. We show results both from multiple imputation analyses and analyses with complete data for each model (non-imputation analyses). STATA SE version 11.1 (Stata Corp, College Station, TX) was used and sample weights were applied when estimating HR.

Table 1.

Characteristics of the subjects by mortality rate: the Aichi Gerontological Evaluation Study (AGES), Aichi, Japan, 2003-2008

Man Woman
N Incidence/person-year Incidence rate (95% CI) (1000 person-years) N Incidence/person-year Incidence rate (95% CI) (1000 person-years)
Age
 65-69 2528 164/10978 14.9 (12.8-17.4) 2325 62/10285 6.0 (4.7-7.7)
 70-74 1982 181/8524 21.2 (18.4-24.6) 1908 76/8377 9.1 (7.2-11.4)
 75-79 1272 214/5288 40.5 (35.4-46.3) 1510 102/6533 15.6 (12.9-19.0)
 80-84 516 138/2035 67.8 (57.4-80.1) 715 82/3029 27.1 (21.8-33.6)
 85 or older 210 93/746 124.6 (101.7-152.7) 344 102/1336 76.3 (62.9-92.7)
Education (years)
 <6 154 31/628 49.3 (34.7-70.1) 407 60/1710 35.1 (27.2-45.2)
 6-9 3322 441/14046 31.4 (28.6-34.5) 3695 212/16108 13.2 (11.5-15.1)
 10-12 1755 179/7493 23.9 (20.6-27.7) 1959 109/8523 12.8 (10.6-15.4)
 ≥13 885 83/3764 22.1 (17.8-27.3) 343 15/1487 10.1 (6.1-16.7)
 Missing 392 56/1641 34.1 (26.3-44.3) 398 28/1733 16.2 (11.2-23.4)
Individual-level equivalent income ($)
 <15,000 1111 166/4634 35.8 (30.8-41.7) 1361 88/5889 14.9 (12.1-18.4)
 15,000-19,999 1132 116/4826 24.0 (20.0-28.8) 812 38/3563 10.7 (7.8-14.7)
 20,000-24,999 1364 171/5751 29.7 (25.6-34.5) 949 49/4155 11.8 (8.9-15.6)
 25,000-29,999 337 43/1415 30.4 (22.5-41.0) 295 19/1276 14.9 (9.5-23.3)
 30,000-39,999 1089 103/4695 21.9 (18.1-26.6) 804 42/3505 12.0 (8.9-16.2)
 40,000-49,999 382 28/1670 16.8 (11.6-24.3) 367 33/1573 21.0 (14.9-29.5)
 ≥50,000 278 25/1202 20.8 (14.1-30.8) 220 13/942 13.8 (8.0-23.8)
 Missing 815 138/3379 40.8 (34.6-48.3) 1994 142/8657 16.4 (13.9-19.3)
Self-rated health
 Very good 562 41/2440 16.8 (12.4-22.8) 489 22/2121 10.4 (6.8-15.8)
 Good 4161 377/17902 21.1 (19.0-23.3) 4367 224/19099 11.7 (10.3-13.4)
 Poor 1416 257/5842 44.0 (38.9-49.7) 1541 133/6633 20.0 (16.9-23.8)
 Very poor 300 99/1121 88.3 (72.5-107.6) 268 35/1112 31.5 (22.6-43.8)
 Missing 69 16/267 60.0 (36.8-98.0) 137 10/595 16.8 (9.0-31.2)
Self-reported BMI
 <18.5 464 116/1835 63.2 (52.7-75.9) 553 70/2333 30.0 (23.7-37.9)
 18.5-24.9 4527 511/19269 26.5 (24.3-28.9) 4378 240/19067 12.6 (11.1-14.3)
 25-29.9 1249 106/5388 19.7 (16.3-23.8) 1372 63/6028 10.5 (8.2-13.4)
 ≥30 74 8/317 25.2 (12.6-50.5) 142 5/631 7.9 (3.3-19.0)
 Missing 194 49/764 64.2 (48.5-84.9) 357 46/1503 30.6 (22.9-40.9)
Present illness
 No illness 1155 84/5015 16.7 (13.5-20.7) 1056 43/4632 9.3 (6.9-12.5)
 Having illness but need no treatment 743 82/3179 25.8 (20.8-32.0) 547 33/2378 13.9 (9.9-19.5)
 Having illness but discontinued treatment 404 51/1701 30.0 (22.8-39.4) 448 18/1965 9.2 (5.8-14.5)
 Receiving some treatment 3957 545/16599 32.8 (30.2-35.7) 4337 304/18780 16.2 (14.5-18.1)
 Missing 249 28/1076 26.0 (18.0-37.7) 414 26/1806 14.4 (9.8-21.1)
Alcohol consumption
 None 2787 433/11555 37.5 (34.1-41.2) 5791 369/25173 14.7 (13.2-16.2)
 Do not drink everyday 1156 110/4973 22.1 (18.3-26.7) 589 31/2563 12.1 (8.5-17.2)
 Drink every day (35 g of alcohol or less) 1885 175/8121 21.6 (18.6-25.0) 235 10/1018 9.8 (5.3-18.3)
 Drink every day (more than 35 g of alcohol) 572 51/2482 20.6 (15.6-27.0) 22 1/92 10.8 (1.5-76.8)
 Missing 108 21/442 47.5 (31.0-72.9) 165 13/714 18.2 (10.6-31.4)
Smoking status
 Non-smoker 1772 179/7584 23.6 (20.4-27.3) 6016 355/26191 13.6 (12.2-15.0)
 Quit 2991 339/12696 26.7 (24.0-29.7) 271 22/1157 19.0 (12.5-28.9)
 Current 1499 220/6297 34.9 (30.6-39.9) 172 20/729 27.4 (17.7-42.5)
 Missing 246 52/994 52.3 (39.9-68.6) 343 27/1483 18.2 (12.5-26.5)
Exercise
 Walking less than 30 minutes walk a day 2120 344/8789 39.1 (35.2-43.5) 2176 165/9414 17.5 (15.0-20.4)
 Walking 30-60 minutes walk a day 2222 246/9477 26.0 (22.9-29.4) 2101 136/9105 14.9 (12.6-17.7)
 Walking 60-90 minutes walk a day 906 74/3908 18.9 (15.1-23.8) 769 25/3378 7.4 (5.0-11.0)
 Walking 90 or more minutes walk a day 799 58/3472 16.7 (12.9-21.6) 788 38/3443 11.0 (8.0-15.2)
 Missing 461 68/1926 35.3 (27.8-44.8) 968 60/4221 14.2 (11.0-18.3)
Total 6508 790/27572 28.7 (26.7-30.7) 6802 424/29561 14.3 (13.0-15.8)
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Table 2.

Characteristics of the subjects according to social capital and mortality rate: the Aichi Gerontological Evaluation Study (AGES), Aichi, Japan, 2003-2008

Man Woman
N Incidence/person-year Incidence rate (95% CI) (1000 person-years) N Incidence/person-year Incidence rate (95% CI) (1000 person-years)
General trust
 Generally speaking, would you say that most people can be trusted or you cannot be too careful in dealing with people? Yes (High SC) 2121 252/9007 28.0 (24.7-31.7) 1448 86/6290 13.7 (11.1-16.9)
Depends 3667 422/15577 27.1 (24.6-29.8) 4480 287/19452 14.8 (13.1-16.6)
No (Low SC) 545 80/2274 35.2 (28.3-43.8) 667 31/2937 10.6 (7.4-15.0)
Missing 175 36/713 50.5 (36.4-70.0) 207 20/882 22.7 (14.6-35.1)
 Would you say that most of the time people try to be helpful or that they are mostly looking out for themselves? Yes (High SC) 1954 227/8291 27.4 (24.0-31.2) 1791 95/7817 12.2 (9.9-14.9)
Depends 3710 412/15796 26.1 (23.7-28.7) 4104 254/17826 14.2 (12.6-16.1)
No (Low SC) 645 106/2675 39.6 (32.8-47.9) 637 50/2760 18.1 (13.7-23.9)
Missing 199 45/810 55.5 (41.5-74.4) 270 25/1159 21.6 (14.6-31.9)
 Do you think that most people would try to take advantage of you if they got the chance, or would they try to be fair? Yes (Low SC) 797 101/3377 29.9 (24.6-36.4) 616 40/2689 14.9 (10.9-20.3)
Depends 3418 378/14536 26.0 (23.5-28.8) 3558 210/15475 13.6 (11.9-15.5)
No (High SC) 2093 263/8847 29.7 (26.3-33.5) 2318 143/10073 14.2 (12.1-16.7)
Missing 200 48/812 59.1 (44.5-78.4) 310 31/1323 23.4 (16.5-33.3)
Social support
 Do you have someone who listens to your concerns and complaints? Yes (High SC) 5267 605/22392 27.0 (24.9-29.3) 5995 360/26087 13.8 (12.4-15.3)
No (Low SC) 878 122/3671 33.2 (27.8-39.7) 424 34/1819 18.7 (13.4-26.2)
Missing 363 63/1508 41.8 (32.6-53.5) 383 30/1655 18.1 (12.7-25.9)
 Do you have someone who looks after you when you are sick and stay in bed for a few days? Yes (High SC) 5967 713/25308 28.2 (26.2-30.3) 5988 372/26045 14.3 (12.9-15.8)
No (Low SC) 258 29/1081 26.8 (18.6-38.6) 485 23/2112 10.9 (7.2-16.4)
Missing 283 48/1182 40.6 (30.6-53.9) 329 29/1404 20.6 (14.3-29.7)
 Do you have someone who acknowledges your existence and value? Yes (High SC) 5705 664/24243 27.4 (25.4-29.6) 5849 357/25440 14.0 (12.7-15.6)
No (Low SC) 433 65/1798 36.2 (28.4-46.1) 379 30/1628 18.4 (12.9-26.3)
Missing 370 61/1532 39.8 (31.0-51.2) 574 37/2492 14.8 (10.8-20.5)
Generalised reciprocity
 Do you listen to someone's concerns and complaints? Yes (High SC) 4945 522/21122 24.7 (22.7-26.9) 5348 282/23326 12.1 (10.8-13.6)
No (Low SC) 1153 197/4748 41.5 (36.1-47.7) 941 107/4000 26.8 (22.1-32.3)
Missing 410 71/1701 41.7 (33.1-52.7) 513 35/2235 15.7 (11.2-21.8)
 Do you look after someone when he/she is sick and stays in bed for a few days? Yes (High SC) 5690 651/24190 26.9 (24.9-29.1) 5785 324/25209 12.9 (11.5-14.3)
No (Low SC) 461 78/1901 41.0 (32.9-51.2) 526 53/2242 23.6 (18.1-30.9)
Missing 357 61/1481 41.2 (32.0-52.9) 491 47/2109 22.3 (16.7-29.7)
Social network
 Political group participation Yes (High SC) 665 72/2848 25.3 (20.1-31.9) 287 13/1250 10.4 (6.0-17.9)
No (Low SC) 5230 605/22171 27.3 (25.2-29.6) 5622 347/24445 14.2 (12.8-15.8)
Missing 613 113/2553 44.3 (36.8-53.2) 893 64/3866 16.6 (13.0-21.2)
 Industry group participation Yes (High SC) 952 108/4059 26.6 (22.0-32.1) 293 6/1304 4.6 (2.1-10.2)
No (Low SC) 4869 556/20653 26.9 (24.8-29.3) 5510 349/23929 14.6 (13.1-16.2)
Missing 687 126/2860 44.1 (37.0-52.5) 999 69/4327 15.9 (12.6-20.2)
 Volunteer group participation Yes (High SC) 642 45/2796 16.1 (12.0-21.6) 574 22/2522 8.7 (5.7-13.2)
No (Low SC) 5122 613/21678 28.3 (26.1-30.6) 5255 331/22829 14.5 (13.0-16.1)
Missing 744 132/3097 42.6 (35.9-50.5) 973 71/4210 16.9 (13.4-21.3)
 Citizen group participation Yes (High SC) 245 28/1044 26.8 (18.5-38.8) 309 10/1368 7.3 (3.9-13.6)
No (Low SC) 5465 622/23202 26.8 (24.8-29.0) 5470 346/23752 14.6 (13.1-16.2)
Missing 798 140/3326 42.1 (35.7-49.7) 1023 68/4441 15.3 (12.1-19.4)
 Religious group participation Yes (High SC) 738 81/3152 25.7 (20.7-31.9) 698 38/3031 12.5 (9.1-17.2)
No (Low SC) 5021 580/21288 27.2 (25.1-29.6) 5151 319/22391 14.2 (12.8-15.9)
Missing 749 129/3131 41.2 (34.7-49.0) 953 67/4139 16.2 (12.7-20.6)
 Sports group participation Yes (High SC) 1282 87/5602 15.5 (12.6-19.2) 1152 36/5074 7.1 (5.1-9.8)
No (Low SC) 4458 564/18776 30.0 (27.7-32.6) 4642 319/20118 15.9 (14.2-17.7)
Missing 768 139/3193 43.5 (36.9-51.4) 1008 69/4369 15.8 (12.5-20.0)
 Neighborhood group participation Yes (High SC) 3445 384/14716 26.1 (23.6-28.8) 3583 199/15657 12.7 (11.1-14.6)
No (Low SC) 2531 308/10650 28.9 (25.9-32.3) 2557 170/11058 15.4 (13.2-17.9)
Missing 532 98/2206 44.4 (36.4-54.1) 662 55/2846 19.3 (14.8-25.2)
 Avocation group participation Yes (High SC) 1592 126/6882 18.3 (15.4-21.8) 2054 75/9046 8.3 (6.6-10.4)
No (Low SC) 4192 533/17671 30.2 (27.7-32.8) 3819 285/16483 17.3 (15.4-19.4)
Missing 724 131/3019 43.4 (36.6-51.5) 929 64/4032 15.9 (12.4-20.3)
 How often do you meet your friend? Once or more/month 4360 448/18691 24.0 (21.8-26.3) 5301 296/23134 12.8 (11.4-14.3)
Several times/year 1077 145/4513 32.1 (27.3-37.8) 610 31/2654 11.7 (8.2-16.6)
Rarely 752 141/3054 46.2 (39.1-54.5) 529 59/2231 26.4 (20.5-34.1)
Having no friends 151 24/620 38.7 (25.9-57.7) 125 22/508 43.3 (28.5-65.8)
Missing 168 32/694 46.1 (32.6-65.2) 237 16/1034 15.5 (9.5-25.3)
Total 6508 790/27572 28.7 (26.7-30.7) 6802 424/29561 14.3 (13.0-15.8)
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Results

The average follow-up period was 4.29 years (SD = 0.75). During 27,571 person-years of follow-up for men and 29,561 person-years of follow-up for women, 790 all-cause deaths in men and 424 in women were observed. The incidence rate per 1000 person-years (IR) of death was 28.7 in men and 14.3 in women. Table 1 and 2 show the distribution of the number of deaths and IR according to covariates and social capital variables. Participants with low social capital in terms of generalised reciprocity and social network tended to have higher IR.

Table 3 shows the univariate and covariates adjusted mortality HRs for the different social capital variables among men. The results of multiple imputation models and non-imputation models were similar, particularly in the univariate models, but the 95%CIs were wider in most of the estimates obtained from the imputation models. In the univariate models using multiple imputation, lower social capital was significantly related to higher mortality in one general trust variable (people try to be helpful: HR = 1.42 (95%CI = 1.01-2.00)), all generalised reciprocity variables (listen to someone's concerns: HR = 1.59 (95%CI = 1.24-2.04); look after someone: HR = 1.49 (95%CI = 1.12-2.00)) and four social network variables (volunteer: HR = 1.78 (95%CI = 1.34-2.37); sports: HR = 1.89 (95%CI = 1.28-2.80); leisure: HR = 1.64 (95%CI = 1.21-2.20); meet friends rarely: HR = 1.99 (95%CI = 1.72-2.31)). When adjusting these models for covariates, only one low social network variable was found to be related to higher mortality (meet friends rarely: HR = 1.30 (95%CI = 1.10-1.53)), while the respective findings for two other social network variables (volunteering and leisure) were marginally not significant

Table 3.

Univariate and covariate adjusted hazard ratios and 95% confidence intervals for all-cause mortality according to social capital

Univariate (imputation) Univariate (non-imputation) Covariate adjusted (imputation) Covariate adjusted (non-imputation)
HR 95%CI HR 95%CI HR 95%CI HR 95%CI
General trust
 Generally speaking, would you say that most people can be trusted? (Ref; Yes (High SC)) Depends 0.96 (0.77-1.20) 0.97 (0.80-1.17) 0.90 (0.69-1.16) 1.01 (0.77-1.33)
No (Low SC) 1.24 (0.91-1.70) 1.25 (0.96-1.63) 1.01 (0.74-1.36) 0.96 (0.65-1.42)
 Would you say that most of the time people try to be helpful? (Ref; Yes (High SC)) Depends 1.00 (0.84-1.20) 1.01 (0.87-1.16) 0.92 (0.78-1.08) 1.00 (0.86-1.16)
No (Low SC) 1.42 (1.01-2.00) * 1.41 (1.06-1.87) * 1.20 (0.83-1.74) 1.06 (0.69-1.63)
 Do you think most people would try to take advantage of you if they got a chance? (Ref; Yes (Low SC)) Depends 0.91 (0.63-1.33) 0.92 (0.65-1.30) 1.01 (0.61-1.68) 1.00 (0.57-1.73)
Social support
 Do you have someone who listens to your concerns and complaints? (Ref; Yes (High SC)) No (Low SC) 1.33 (0.79-2.23) 1.33 (0.80-2.20) 1.09 (0.61-1.95) 1.17 (0.63-2.15)
 Do you have someone who looks after you when you are sick and stay in bed for a few days? (Ref; Yes (High SC)) No (Low SC) 1.06 (0.70-1.61) 1.06 (0.71-1.58) 0.84 (0.58-1.22) 0.87 (0.50-1.52)
 Do you have someone who acknowledges your existence and value? (Ref; Yes (High SC)) No (Low SC) 1.49 (0.99-2.25) 1.48 (0.95-2.30) 1.18 (0.67-2.08) 1.33 (0.70-2.54)
General reciprocity
 Do you listen to someone's concerns and complaints? (Ref; Yes (High SC)) No (Low SC) 1.59 (1.24-2.04) * 1.58 (1.31-1.91) * 1.27 (0.95-1.70) 1.03 (0.70-1.51)
 Do you look after someone when he/she is sick and stays in bed for a few days? (Ref; Yes (High SC)) No (Low SC) 1.49 (1.12-2.00) * 1.44 (1.13-1.83) * 1.01 (0.78-1.32) 0.83 (0.70-0.98) *
Social network
 Political organization or group (Ref; yes) No (Low SC) 1.14 (0.83-1.56) 1.11 (0.85-1.46) 0.99 (0.71-1.39) 1.11 (0.83-1.49)
 Industrial or trade association (Ref; yes) No (Low SC) 1.04 (0.72-1.51) 1.02 (0.80-1.29) 0.88 (0.59-1.30) 0.91 (0.62-1.35)
 Volunteer group (Ref; yes) No (Low SC) 1.78 (1.34-2.37) * 1.75 (1.39-2.21) * 1.30 (0.95-1.77) 1.51 (1.19-1.91) *
 Citizen or consumer group (Ref; yes) No (Low SC) 1.05 (0.59-1.86) 0.98 (0.57-1.68) 0.79 (0.43-1.47) 0.95 (0.37-2.40)
 Religious organization or group (Ref; yes) No (Low SC) 1.10 (0.77-1.56) 1.11 (0.79-1.56) 1.21 (0.86-1.70) 1.30 (1.06-1.58) *
 Sports group or club (Ref; yes) No (Low SC) 1.89 (1.28-2.80) * 1.98 (1.52-2.58) * 1.32 (0.78-2.21) 1.44 (1.10-1.88) *
 Neighbourhood association / Senior citizen club / Fire-fighting team (Ref; yes) No (Low SC) 1.16 (0.94-1.42) 1.15 (0.95-1.39) 1.12 (0.90-1.40) 1.20 (0.80-1.81)
 Leisure activity group (Ref; yes) No (Low SC) 1.64 (1.21-2.20) * 1.59 (1.40-1.81) * 1.29 (0.94-1.77) 1.27 (1.04-1.55) *
 How often do you meet your friends? (Ref; Once or more/month) Several/year 1.26 (0.96-1.67) 1.26 (0.99-1.60) 1.09 (0.77-1.56) 1.06 (0.75-1.48)
Rarely 1.99 (1.72-2.31) * 1.99 (1.75-2.25) * 1.30 (1.10-1.53) * 1.38 (1.28-1.49) *
Having no friend 1.43 (0.79-2.56) 1.41 (0.90-2.20) 0.77 (0.47-1.26) 0.49 (0.19-1.26)
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Multiple imputation Cox proportional hazard models: the Aichi Gerontological Evaluation Study (AGES), Aichi, Japan, 2003-2008, Men1.

1 Adjusted for age, BMI, self-rated health, current illness, smoking history, alcohol consumption, exercise, equivalent income and education.

* Statistically significant variable (p < 0.05).

Table 4 shows the univariate and covariates adjusted mortality HRs for the different social capital variables among women. The results of multiple imputation models and non-imputation models were also similar, particularly in the univariate models, but the 95%CIs were wider in most of the estimates obtained from the imputation models. In the univariate multiple imputation models, lower social capital was significantly related to higher mortality in all generalised reciprocity variables (listen to someone's concerns: HR = 2.31 (95%CI = 1.49-3.58) and look after someone: HR = 1.71 (95%CI = 1.18-2.47)) and four social network variables (sports: HR = 2.32 (95%CI = 1.41-3.82); leisure: HR = 2.24 (95%CI = 1.36-3.68); meet friends rarely: HR = 2.41 (95%CI = 1.31-4.45); having no friends: HR = 3.40 (95%CI = 2.10-5.52)). In the covariate adjusted multiple imputation analysis, only one lower social network response related to higher mortality (having no friends: HR = 1.81 (95%CI = 1.02-3.23)), while findings for one generalised reciprocity variable (listen to someone's concerns) and one social network variable (leisure) were marginally not significant. Interestingly, the response indicating lower social capital in one general trust variable was significantly related to lower mortality (most people cannot be trusted; HR = 0.65 (95%CI = 0.45-0.96)).

Table 4.

Univariate and covariate adjusted hazard ratios and 95% confidence intervals for all-cause mortality according to social capital

Univariate (imputation) Univariate (non-imputation) Covariate adjusted (imputation) Covariate adjusted (non-imputation)
HR 95%CI HR 95%CI HR 95%CI HR 95%CI
General trust
 Generally speaking, would you say that most people can be trusted? (Ref; Yes (High SC)) Depends 0.98 (0.67-1.43) 0.99 (0.70-1.42) 0.98 (0.65-1.50) 0.97 (0.79-1.18)
No (Low SC) 0.80 (0.55-1.16) 0.80 (0.60-1.05) 0.65 (0.45-0.96) * 0.62 (0.42-0.93) *
 Would you say that most of the time people try to be helpful? (Ref; Yes (High SC)) Depends 1.26 (0.81-1.95) 1.27 (0.84-1.92) 1.29 (0.72-2.32) 0.95 (0.67-1.34)
No (Low SC) 1.69 (1.00-2.87) 1.72 (1.07-2.77) * 1.49 (0.84-2.64) 1.29 (0.99-1.67)
 Do you think most people would try to take advantage of you if they got a chance? (Ref; Yes (Low SC)) Depends 0.94 (0.54-1.65) 0.94 (0.60-1.48) 1.15 (0.60-2.22) 0.90 (0.41-1.95)
No (High SC) 1.10 (0.49-2.49) 1.11 (0.52-2.38) 1.33 (0.49-3.60) 1.21 (0.42-3.50)
Social support
 Do you have someone who listens to your concerns and complaints? (Ref; Yes (High SC)) No (Low SC) 1.36 (0.80-2.30) 1.36 (0.86-2.14) 1.11 (0.62-1.99) 1.22 (0.57-2.61)
 Do you have someone who looks after you when you are sick and stay in bed for a few days? (Ref; Yes (High SC)) No (Low SC) 0.86 (0.60-1.24) 0.86 (0.59-1.26) 0.84 (0.50-1.43) 0.85 (0.45-1.60)
 Do you have someone who acknowledges your existence and value? (Ref; Yes (High SC)) No (Low SC) 1.31 (0.65-2.66) 1.32 (0.74-2.36) 1.05 (0.56-1.95) 0.91 (0.55-1.51)
Generalised reciprocity
 Do you listen to someone's concerns and complaints? (Ref; Yes (High SC)) No (Low SC) 2.31 (1.49-3.58) * 2.38 (1.56-3.63) * 1.57 (0.96-2.55) 1.40 (0.71-2.77)
 Do you look after someone when he/she is sick and stays in bed for a few days? (Ref; Yes (High SC)) No (Low SC) 1.71 (1.18-2.47) * 1.72 (1.23-2.39) * 0.92 (0.63-1.35) 0.73 (0.51-1.05)
Social network
 Political organization or group (Ref; yes) No (Low SC) 1.55 (0.58-4.09) 1.55 (0.79-3.02) 1.25 (0.42-3.76) 1.48 (0.63-3.46)
 Industrial or trade association (Ref; yes) No (Low SC) 2.92 (0.58-14.64) 4.19 (1.46-12.02) * 1.95 (0.38-9.97) 2.51 (0.77-8.14)
 Volunteer group (Ref; yes) No (Low SC) 1.76 (0.81-3.83) 1.75 (1.09-2.80) * 1.06 (0.38-2.95) 0.95 (0.54-1.67)
 Citizen or consumer group (Ref; yes) No (Low SC) 1.76 (0.45-6.90) 2.07 (1.00-4.30) 1.14 (0.21-6.11) 0.92 (0.56-1.51)
 Religious organization or group (Ref; yes) No (Low SC) 1.17 (0.77-1.80) 1.19 (0.95-1.50) 1.25 (0.73-2.14) 1.54 (0.84-2.85)
 Sports group or club (Ref; yes) No (Low SC) 2.32 (1.41-3.82) * 2.33 (1.72-3.17) * 1.42 (0.78-2.59) 1.72 (1.11-2.68) *
 Neighbourhood association / Senior citizen club / Fire-fighting team (Ref; yes) No (Low SC) 1.19 (0.94-1.52) 1.22 (1.03-1.44) * 1.11 (0.86-1.43) 1.19 (0.95-1.48)
 Leisure activity group (Ref; yes) No (Low SC) 2.24 (1.36-3.68) * 2.32 (1.52-3.54) * 1.54 (0.92-2.57) 1.60 (1.10-2.32) *
 How often do you see your friends? (Ref; Once or more/month) Several/year 1.00 (0.64-1.58) 0.99 (0.68-1.42) 0.92 (0.58-1.46) 0.87 (0.40-1.87)
 Rarely 2.41 (1.31-4.45) * 2.44 (1.40-4.26) * 1.64 (0.90-2.98) 1.62 (0.82-3.22)
 Having no friend 3.40 (2.10-5.52) * 3.55 (2.37-5.32) * 1.81 (1.02-3.23) * 2.10 (0.71-6.26)
Open in a new tab

Multiple imputation Cox proportional hazard models: the Aichi Gerontological Evaluation Study (AGES), Aichi, Japan, 2003-2008, Women1.

1 Adjusted for age, BMI, self-rated health, current illness, smoking history, alcohol consumption, exercise, equivalent income and education.

* Statistically significant variable (p < 0.05).

Discussion

To the best of our knowledge, this study is the first prospective cohort study to assess the relationships between various social capital measures and mortality. In addition, this is the first cohort study on the relationship between social capital and mortality in a non-Western country. The present study showed that the structural social capital variable (friendship network) was a good predictor for all-cause mortality among older Japanese. Among men, it was the frequency of meetings with friends that was important, with those meeting their friends rarely having higher mortality, while was it was the lack of friends that was indicative of higher mortality among women. In addition, low general trust was related to lower mortality among women, suggesting that general trust has a different meaning among older Japanese women than among men.

Our results suggested the existence of culture differences in the association between trust and health. In addition, it is possible that the specific questions used to measure trust may also play a role. In our study, the question about general trust ("Generally speaking, would you say that most people can be trusted?") measures the trust for strangers, not group members [28]. In Japan, a relatively collectivist society with intense group ties, human relations are based on mutual assurance between group members rather than mutual trust between out-group members [11,13]. The systems of mutual assurance, monitoring and sanctioning, within groups make the Japanese society safe and stable though closed [11,13]. In such a society with strong ties, people can relatively easily obtain social support [29]. Though Japanese society is gradually changing recently because of globalisation, older people have lived in this traditional type of society for a long time throughout their life-course. Our results could suggest that Japanese older women who did not trust others would adapt well to the collectivist society with intense group ties and benefit from the society. In this Japanese older generation, men tended to work outside while women were predominantly housewives, therefore, men had to communicate with out-group members during their work and this may have contributed to developing their general trust towards strangers. In contrast, lower general trust measured by the question "Would you say that most of the time people try to be helpful?" tended to be associated with higher mortality among both men and women. This may be a more applicable question for measuring general trust among older Japanese, as this cohort may refer to their group members as "people" when answering this question. Previous cohort studies have not used general questions on trusting people to measure social capital. In Finland, a prospective study determined the beneficial effect of trust on all-cause mortality among women aged 30-99 years, not men [2]. Their measure of trust was based on the number of and trust in close friends. In this study, we did not use the factor/principal component analysis to check the association between detailed, not combined, social capital variables and mortality. As the results, various social capital variables were included into the models and different association of trust questions on mortality were shown though this method had the possibility of a type 1 error. Further prospective research assessing trust and mortality with considering various culture backgrounds is needed.

Our results are partially consistent with those of previous studies. Social network and social support are positively associated with health. A meta-analysis of social relationships and mortality determined that strong structural social relationships (social network) and functional social relationships (social support) increased the likelihood of survival [30]. In line with this, our study showed significant associations between friendship network and mortality (meet friends rarely for men; HR = 1.30 (95%CI = 1.10-1.53), having no friends for women; HR = 1.81 (95%CI = 1.02-3.23)); however, social support was not significantly associated with mortality. Although we considered diagnosed diseases and excluded from our study people with limitations in basic activities of daily living, it is possible that people included in the study may have had latent fatal diseases and consequently needed some help; this may have affected our results about social support and mortality. The concept of generalised reciprocity is based on the assumption that when people provide resources, good turns will be repaid at some unspecified time in the future, perhaps even by an stranger [31]. It does not entail tit-for-tat calculations in which individuals can be sure that a good turn will be repaid quickly and automatically [31]. Therefore, we used variables about the provision of social support as generalised reciprocity variables. In our study, generalised reciprocity showed marginal though non-significant association with mortality (HR = 1.27 (95%CI = 0.95-1.70) for men and HR = 1.57 (95%CI = 0.96-2.55) for women). A prospective cohort study in Finland showed that leisure participation was significantly though marginally associated with reduced all-cause mortality (HR = 0.94 (95%CI = 0.89-1.00) for men and HR = 0.96 (95%CI = 0.91-1.00) for women). In our study, covariate adjusted HRs of leisure participation were again marginal, though non-significant (HR = 1.29 (95%CI = 0.94-1.77) for men and HR = 1.54 (95%CI = 0.92-2.57) for women). The meaning of volunteering varies in the societies of different cultures [8] and relationships between volunteering and mortality are not consistent across studies [3-5]. In our study, covariate adjusted HR of volunteer participation was marginal though non-significant for men (HR = 1.30 (95%CI = 0.95-1.77)) and non-significant for women (HR = 1.06 (95%CI = 0.38-2.95)).

There are several plausible pathways linking social capital to health [32]. At first, social capital may affect individual health by influencing health-related behaviours through promotion of more rapid diffusion of health information and by exerting social control over deviant health-related behaviours [32]. Second, higher social capital may promote health by increasing access to local services and amenities [32]. Good access to service such as transportation, clinics and community health centres could improve health. Third, there are associations between social capital and psychological distress [33,34]. Social networks and social support can buffer the negative effects of life events on mental health [34]. Fourth, the communities with higher social capital produce more egalitarian patterns of political participation that result in the implementation of policies which ensure the security of all its members [32].

The results of this study have important public health implications. Among older Japanese, structural social capital variable related to friendship network were found to be significantly associated with mortality regardless of various covariates. This result suggests the possibility that public investment to promote social network may reduce the mortality among older people.

Our study has a number of limitations and strengths. The follow-up period (4.29 years) was relatively short. There was a potential bias caused by latent fatal disease though we considered diagnosed diseases and limitations in basic activities of daily living at baseline. In addition, the response rate was 50.4%; therefore, the results may have been affected by selection bias. Hanibuchi et al. previously conducted ecological analysis that assessed associations between community-level social capital and response rate using another data set from the AGES project and found that higher response rates were significantly associated with higher social capital [35]. Therefore, respondents of this study might have higher social capital than non-respondents. Although our results showed significant effects of some dimensions of social capital on all-cause mortality, this low response rate might have attenuated that association. In addition, compared with government data, our study respondents tended to be younger. It could be argued that healthier and younger people tend to respond to our questionnaire while people with higher risks of mortality tend to not participate. If so, this might have contributed to an underestimation of the association between poor social capital and mortality. As a strength, the present study used various social capital variables. Although the validity and reliability of the social capital variables were not been directly examined, a previous study using AGES project data checked the association between social capital variables based on our survey and voting rate, rate of volunteer registration and rate of social participation based on public social survey data [35]. Mean response of trust variable measured by our survey significantly associated with rate of volunteer registration in each community. Similarly, social network variables were significantly associated with voting rate.

Conclusions

In conclusion, friendship network, a measure of individual social capital, was a good predictor for all-cause mortality among older Japanese. In addition, low general trust was related to lower mortality among women. Further studies examining the different effect of social capital between Western and non-Western countries are needed.

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

JA had the idea for the study, participated in its design, performed the statistical analysis and drafted the manuscript as a principal author. KK helped develop the idea of the study, participated in acquiring the data and with design, and edited the manuscript. HH participated in acquiring the data and critically revising the manuscript. SVS participated in design of study, data analysis and critically revised the manuscript. CM, NK, YI, KS and KO participated in design of study and critically revised the manuscript. All authors read and approved the final manuscript.

Pre-publication history

The pre-publication history for this paper can be accessed here:

http://www.biomedcentral.com/1471-2458/11/499/prepub

Contributor Information

Jun Aida, Email: j-aida@umin.ac.jp.

Katsunori Kondo, Email: kkondo@n-fukushi.ac.jp.

Hiroshi Hirai, Email: hirai181kan@gmail.com.

S V Subramanian, Email: SVSUBRAM@hsph.harvard.edu.

Chiyoe Murata, Email: cmurata@hama-med.ac.jp.

Naoki Kondo, Email: nkondo@yamanashi.ac.jp.

Yukinobu Ichida, Email: ichida@doctoral.jp.

Kokoro Shirai, Email: kshirai@hsph.harvard.edu.

Ken Osaka, Email: osaka@m.tohoku.ac.jp.

Acknowledgements

This study used data from the Aichi Gerontological Evaluation Study (AGES). This survey was conducted by the Nihon Fukushi University Center for Well-being and Society as one of their research projects, and supported by a grant of Strategic Research Foundation Grant-aided Project for Private Universities from Ministry of Education, Culture, Sport, Science, and Technology, Japan (MEXT), 2009-2013.

The authors wish to thank Dr. Tomoya Hanibuchi and Dr. Georgios Tsakos for helpful comments on an earlier draft.

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